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Edge enhancement

About: Edge enhancement is a research topic. Over the lifetime, 2324 publications have been published within this topic receiving 30962 citations.


Papers
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Proceedings ArticleDOI
25 Mar 2013
TL;DR: The novel vessel segmentation method starts with the contrast adjustment of the green channel image representation to increase the dynamic range of the gray levels, so that the vessels will appear brighter than the background.
Abstract: Digital images are obtained from the retina and graded by trained professionals. However, a significant shortage of professional observers has prompted computer assisted monitoring. Assessment of blood vessels network plays an important role in a variety of medical disorders. Manifestations of several vascular disorders, such as diabetic retinopathy and hypertensive retinopathy depend on detection of the blood vessels network. The novel vessel segmentation method starts with the contrast adjustment of the green channel image representation to increase the dynamic range of the gray levels, so that the vessels will appear brighter than the background. A multi-scale method for retinal image contrast enhancement based on the Curvelet transform is employed on the contrast adjusted image. The Curvelet transform has better performance in representing edges than wavelets for its anisotropy and directionality, and is therefore well-suited for multi-scale edge enhancement. The Curvelet coefficients in corresponding subbands are modified via a nonlinear function and take the noise into account for more precise reconstruction and better visualization. The morphological operators are used to smoothen the background, allowing vessels, to be seen clearly and to eliminate the non-vessel pixels. The described techniques in this work are applied on images from eye hospital. The proposed algorithm being simple and easy to implement, is best suited for fast processing applications.

18 citations

Proceedings ArticleDOI
28 Sep 2015
TL;DR: The intent of this paper is to provide a first critical review to some contrast enhancement evaluation measures and propose a new one and is considered as a first step towards the development of a unifying framework for image enhancement evaluation.
Abstract: Contrast enhancement is one of the most studied problems in image processing. A plethora of approaches has been proposed in the literature for image enhancement since the pioneer work of Kovasznay and Joseph in 1955 [1] and the famous contribution of Gabor in 1965 on image deblurring [2]. However, very few works have been dedicated to contrast enhancement evaluation. This is mainly due to the fact that image enhancement is primarily related to subjective aspects of human perceptual vision. The intent of this paper is to provide a first critical review to some contrast enhancement evaluation measures and propose a new one. An objective comparison of these measures on various color real images processed by some neighborhood based methods is provided. This work is considered as a first step towards the development of a unifying framework for image enhancement evaluation. This could be also used to control the side effect that may result from any image enhancement such as contrast enhancement, denoising, tone mapping and other similar image processing tools.

18 citations

Patent
26 Feb 2010
TL;DR: In this paper, an image enhancement method and an apparatus for distortion correction by air particle like fog are provided to effectively eliminate scattered light into the air, where the scattered light map generation part(120) creates the atmosphere scattered light maps based on the average of the first brightness signal and rate of the standard deviation.
Abstract: PURPOSE: An image enhancement processing method and an apparatus for distortion correction by air particle like fog are provided to effectively eliminate scattered light into the air. CONSTITUTION: The scattered light map generation part(120) creates the atmosphere scattered light map based on the average of the first brightness signal and rate of the standard deviation. The subtraction unit(130) subtracts scattered light map from the brightness signal of Y/C transform unit(110). The edge enhancement part(140) performs the edge enhancement processing toward the brightness signal of the subtraction unit. The post processing unit(160) performs the histogram stretching about the RGB signal of the RGB transform unit(150).

18 citations

Book ChapterDOI
TL;DR: A blurred-mass subtraction technique has been developed for mammography, which enhances small-object contrast and visibility throughout the breast area and an analysis of its capabilities and limitations is given.
Abstract: A blurred-mass subtraction technique has been developed for mammography, which enhances small-object contrast and visibility throughout the breast area. The procedure is easy to implement and requires no additional exposure. Perception of low-contrast objects is improved by eliminating extreme light- and dark-image areas. Contrast of structures within certain portions of the breast is increased by compression into the high-contrast portion of the film characteristic curve. Detail visibility is also increased by the edge enhancement produced by this process. This paper describes the enhancement process and gives an analysis of its capabilities and limitations.

18 citations

Patent
06 Feb 1995
TL;DR: In this article, the authors proposed a method for restoring images that have been distorted due to lossy image compression, which can comply with many compression standards, adds nothing to the compressed images' bandwidth, and distorts the image by only a very tiny amount.
Abstract: Traditional techniques such as filtering and edge enhancement have been applied to restoring images that have been distorted due to lossy image compression. However, these techniques have ignored a unique feature that can be exploited when working with digital compression. Before the image is stored or transmitted, the sender has access to both the original and the distorted images, enabling the encoder to transmit information specifying the regions where the enhancement was successful. To utilize this feature, before storage or transmission the sender produces a codec file, and assesses the efficacy of one or more enhancement schemes. To determine which image regions have been improved by the enhancement, the enhanced codec is compared to the original. A map of where the enhancement scheme was successful is encoded into the image by making tiny adjustments to the image itself. This method can comply with many compression standards, adds nothing to the compressed images' bandwidth, and distorts the image by only a very tiny amount. Examples are presented showing the reduction of distortion if enhancement is used, together with calculations of how much distortion is introduced if a standard decompressor is used.

18 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20231
20228
202148
202061
201947
201851